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02/04/2023
Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting
Data sketching is a critical tool for distinct counting, enabling multis...
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03/29/2022
(Nearly) All Cardinality Estimators Are Differentially Private
We consider privacy in the context of streaming algorithms for cardinali...
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07/10/2021
Few-Shot Domain Adaptation with Polymorphic Transformers
Deep neural networks (DNNs) trained on one set of medical images often e...
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04/11/2021
Simple, Optimal Algorithms for Random Sampling Without Replacement
Consider the fundamental problem of drawing a simple random sample of si...
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11/20/2020
HyperLogLog (HLL) Security: Inflating Cardinality Estimates
Counting the number of distinct elements on a set is needed in many appl...
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07/07/2020
Manifold Learning via Manifold Deflation
Nonlinear dimensionality reduction methods provide a valuable means to v...
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05/05/2020
Conditional Cuckoo Filters
Bloom filters, cuckoo filters, and other approximate set membership sket...
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02/15/2020
Security of HyperLogLog (HLL) Cardinality Estimation: Vulnerabilities and Protection
Count distinct or cardinality estimates are widely used in network monit...
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11/09/2018
Count-Min: Optimal Estimation and Tight Error Bounds using Empirical Error Distributions
The Count-Min sketch is an important and well-studied data summarization...
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03/06/2018
On Nonlinear Dimensionality Reduction, Linear Smoothing and Autoencoding
We develop theory for nonlinear dimensionality reduction (NLDR). A numbe...
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11/27/2017
Family learning: nonparametric statistical inference with parametric efficiency
Hypothesis testing and other statistical inference procedures are most e...
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09/12/2017
Data Sketches for Disaggregated Subset Sum and Frequent Item Estimation
We introduce and study a new data sketch for processing massive datasets...
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09/06/2017
Optimal Sub-sampling with Influence Functions
Sub-sampling is a common and often effective method to deal with the com...
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08/16/2017
Adaptive Threshold Sampling and Estimation
Sampling is a fundamental problem in both computer science and statistic...
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03/15/2012
Online Semi-Supervised Learning on Quantized Graphs
In this paper, we tackle the problem of online semi-supervised learning ...
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01/28/2011